Process with Reverse Supply Chain
A THESIS SUBMITTED IN FULFILMENT OF
THE REQUIREMENT FOR THE AWARD OF THE DEGREE OF
Doctor of Philosophy
IN
MECHANICAL ENGINEERING
BY
Rabindra narayan mahapatra
NATIONAL INSTITUTE OF TECHNOLOGY ROURKELA - 769008, INDIA
July-2013
Dedicated to My
Family
Dr. Bibhuti Bhusan Biswal Professor and Head
Department of Industrial Design NIT, Rourkela
CERTIFICATE
This is to certify that the thesis entitled ―Inventory Models for Manufacturing Process with Reverse Supply Chain‖ being submitted by Rabindra Narayan Mahapatra for the award of the degree of Doctor of Philosophy (Mechanical Engineering) of NIT Rourkela, is a record of bonafide research work carried out by him under my supervision and guidance. He has worked for more than three years on the above problem at the Department of Mechanical Engineering, National Institute of Technology, Rourkela and this has reached the standard fulfilling the requirements and the regulation relating to the degree. The contents of this thesis, in full or part, have not been submitted to any other university or institution for the award of any degree or diploma.
(
Dr. B. B. Biswal
)NATIONAL INSTITUTE OF TECHNOLOGY
ROURKELA, INDIA
ACKNOWLEDGEMENT
It is not possible to prepare a dissertation without the assistance and encouragement of other people. This one is certainly no exception. On the very outset of this report, I would like to extend my sincere and heartfelt obligation towards all the personages who have helped me in this endeavour.
I am ineffably indebted to Dr. Bibhuti Bhusan Biswal, Professor and Head, Department of Industrial Design, NIT, Rourkela for conscientious guidance and encouragement to accomplish this assignment. The successful and timely completion of the work is due to his constant inspiration and constructive criticism. I am also thankful to Dr. S. K. Misra, Professor, SIT, Bhubaneswar, Prof. U. K. Mohanty, Professor, NIT, Rourkela and Prof. M. Masant, Asst. Professor, NIT, Rourkela for their valuable guidance during the research work. I record my gratitude to Mrs. Meenati Biswal for her constant support during my stay at Rourkela.
I am extremely thankful and pay my gratitude to Professor K. P. Maity, Head, Department of Mechanical Engineering, NIT, Rourkela and Professor S. K. Sarangi, Director, NIT, Rourkela for their valuable guidance and support during my work at NIT Rourkela.
I also acknowledge with a deep sense of reverence, my gratitude towards my parents, my wife Reena and daughters Jeny and Rony who have always supported me morally during the tenure of the research programme.
I extend my gratitude to my in-laws for their constant encouragement and support during my stay at Rourkela.
At last but not the least gratitude goes to Mr. Pramod Kumar Parida, Mr.
Bunil Balabantaray, Mr. P. Jha and all my co-research fellows at NIT Rourkela and friends who directly or indirectly helped me to complete this dissertation.
Finally, I thank the one above all, the omnipresent God for giving me strength during the course of the research work.
Any omission in this brief acknowledgement does not mean lack of gratitude.
Rabindra Narayan Mahapatra
ABSTRACT
Technology innovation leading to development of new products and enhancement of features in existing products is happening at a faster pace than ever. This trend has resulted in gross increase in use of new materials and decreased customers‘
interest in relatively older products leading to the deteriorating conditions of the environment due to the reduction of non-renewable resources and steady increase in the land fill of waste. This has forced organizations and communities to consider recovery alternatives such as reuse, repair, recycle, refurbish, remanufacture and cannibalize, rather than discarding of the products after end of life.
Products are retuned back or become redundant because either they do not function properly or functionally they become obsolete. The sources of these returns are Manufacturing returns, Distribution returns and Customer returns. The product recovery options in reverse supply are Repair, Refurbish, Re-manufacture, Cannibalize and Recycle. The main difference between the options is in the reprocessing techniques. Where Repair, refurbishing, and remanufacturing are involved in the up gradation of the used products in quality and/or technology with a difference with respect to the degree of up gradation(repair involves the least, and remanufacturing the largest),the cannibalization and recycling are involved in using parts ,components and materials of the used products.
Although much is being disused on the different recovery options still a lot of research remains to be done for improvement of the currently available techniques.
In this context the present work focuses on remanufacturing option of recovery process for return items which is the most advanced and environmentally friendly production processes in use. Therefore the broad objectives of the present work are to deal with the different models of remanufacturing either new or existing for adding new features to it and making it simple and more user oriented, to develop deterministic models using direct manufacturing and remanufacturing for profit optimization, to develop and deal with probabilistic models of inventory with demand fluctuation using direct manufacturing and remanufacturing.to select and recommend a tool for predicting various critical parameters associated with the Reverse supply chain (RSC).to make these models usable to achieve maximum advantages by reutilization of resources integrating the upstream and downstream chains.
For the effective implementation of remanufacturing in Reverse supply chain, the entire work has been arranged in different chapters to present the distinct aspects of the research. Models are developed with special reference to remanufacturing.
These models proposed helped in minimizing the gaps existing in the RSC in the
present scenario. The different models proposed for RSC are discussed on the basis of deterministic and probabilistic approaches. Although a lot of assumptions are intentionally made to make the models deterministic, still these models have its own identity in satisfying the needs of RSC. Two models are being discussed under deterministic approach. These models tries to find out the amount of new product supply to the market, the amount of remanufactured products supply to the market, the amount of products returned from the market and the amount of waste.
Pertinent data from industry have been considered to prepare the models. The model variables are tested with adaptive-network-based fuzzy inference system (ANFIS), where the testing of the actual out come and desired outcome is done by using ANFIS. One of the proposed models is picked up to predict the critical parameters associated with RSC using remanufacturing.
Although the models dealing with the deterministic RSC models are simple still it becomes difficult to deal with a situation where there is a fluctuation of demand in the market, which is a common phenomenon. Therefore, it becomes inevitable to use the probabilistic approach for sorting out it. The aim is to deal with probabilistic models of inventory and models are proposed where the uncertainty due to fluctuation of demand and uncertainty in the return rate of used products is taken care of by using the safety stock. The determination of the safety stock is done on the basis of service level approach. The model variables are optimized using mathematical models considering the profit maximization.
The contribution of the present work is directed towards the environmental benefits. The manufacture of durable goods is one of the major contributors to the GNP of all developed countries. It employs large amounts of human resources, raw materials and energy. The raw materials and energy in the production of durable goods have been continually depleted. Many durable products are disposed in landfills at the end of their useful lives as well. The landfill space has been decreasing and the price charged by the landfills is increasing at a faster rate. This becomes an environmental concern. Remanufacturing, as discussed earlier is one of the predominant product recovery option for the return products. With respect to quality it is considered to be as good as new ones but with a lower cost of conversion. Therefore, focusing on remanufacturing option of product recovery not only decreases the depletion rate of virgin raw materials and rate of land fill but also contributes much towards the GDP as well as GNP. The models proposed in this work are simple and can be practically implemented to get benefits from the return items and still satisfying the market demand for sustainable production.
Table of Contents
Certificate ... ii
Acknowledgements ... iii
Abstract ... iv-v Table of Contents ... vi-ix List of Tables ... x
List of Figures ... xi-xiv List of Symbols ... xv-xvi Abbreviation ... xvii
1 INTRODUCTION ... 1
1.1 Overview ... 1
1.2 Process views of a supply chain ... 4
1.2.1 Cycle view of supply chain processes ... 4
1.2.2 Push/Pull view of a supply chain processes ... 6
1.3 Reverse supply chain ... 8
1.4 Product returns: the various routes ... 9
1.4.1 Manufacturing returns ... 9
1.4.2 Distribution returns ... 9
1.4.3 Customer returns ... 10
1.5 The Forward Supply Chain vis-à-vis Reverse Supply Chain ... 13
1.5.1 Location theory and logistic network design ... 14
1.5.2 Forecasting ... 15
1.5.3 Inventory control ... 16
1.5.4 Remanufacturing ... 17
1.5.5 Disassembly operations ... 19
1.5.6 Reverse distribution ... 20
1.6 Product recovery in reverse supply chain ... 20
1.6.1 Repair ... 21
1.6.2 Refurbishing ... 21
1.6.3 Remanufacturing ... 21
1.6.4 Cannibalization ... 22
1.6.5 Recycling ... 22
1.7 Examples of Reverse Supply Chains across industries: ... 23
1.7.1 Computer/Electronics industry ... 23
1.7.2 Automotive industry ... 24
1.7.3 Challenges ... 25
1.8 Objective of research ... 26
1.9 Methodology ... 26
1.10 Organization of thesis... 27
1.11 Summary ... 28
2 LITERATURE SURVEY ... 30
2.1 Overview ... 30
2.2 Some important literatures related to the present work... 31
2.3 Supply chain management ... 34
2.4 Reverse supply chain ... 42
2.5 Risk analysis in reverse supply chain ... 44
2.6 Reverse distribution ... 46
2.7 Integration of forward and reverse distribution... 48
2.8 Inventory control in reverse supply chain ... 48
2.8.1 Deterministic models ... 48
2.8.2 Stochastic models in reverse supply chain ... 52
a) Periodic review models:... 52
b) Continuous review models ... 53
2.9 Supply chain management with remanufacturing ... 55
2.10 The Adaptive Network Based Fuzzy Inference System in RSC ... 58
2.11 The Gaps that exist in the previous research ... 60
2.12 Problem statement ... 60
2.13 Summary ... 61
3 AN OVERVIEW OF SUPPLY CHAINS WITH REMANUFACTURING ... 62
3.1 Overview ... 62
3.2 Benefits of remanufacturing ... 63
3.3 Available models of supply chain with remanufacturing method... 63
3.3.1 General framework of remanufacturing ... 64
3.4 Summary ... 71
4 MODELING RSC WITH REMANUFACTURING FOR QUANTITATIVE ANALYSIS ... 73
4.1 Overview ... 73
4.2 Modeling the reverse supply chain with remanufacturing ... 74
4.2.1 Mathematical formulation ... 76
4.2.2 Numerical experiment for a cartridge manufacturing industry ... 79
4.2.3 Numerical experiment for tire manufacturing industry ... 82
4.3 Modeling the reverse supply chain inventory ... 86
4.4 Proposed reverse supply chain model with remanufacturing... 87
4.4.1 Methodology ... 88
4.4.2 Implementation of the outcome ... 91
4.5 Summary ... 93
5 PROBABILISTIC MODELING OF RSC WITH REMANUFACTURING .. 94
5.1 Overview ... 94
5.2 A probabilistic approach for RSC model for remanufacturing ... 95
5.2.1 The conventional inventory model ... 95
5.2.2 The model formulation for optimal manufacturing ... 96
5.2.3 The proposed model ... 97
5.2.4 The model variables for the proposed model ... 98
5.3 A modified RSC with remanufacturing for sustainable product cycle ... 104
5.3.1 Model description ... 105
5.3.2 Model parameters... 105
5.3.3 Mathematical formulation ... 106
5.4 Summary ... 109
6 PREDICTION OF MODEL VARIABLES USING ANFIS ... 110
6.1 Overview ... 110
6.2 Concepts of fuzzy ... 111
6.3 Proposed model for measurement of RSC alertness ... 112
6.4 Designing ANFIS architecture ... 113
6.4.1 Architecture of ANFIS ... 114
6.5 Learning algorithms ... 115
6.6 ANFIS simulation ... 117
6.7 Summary ... 118
7 RESULTS AND DISCUSSIONS ... 119
7.1 Overview ... 119
7.2 Results and discussion for ―Modeling the RSC with remanufacturing‖ ... 119
7.2.1 Analysis for the cartridge manufacturing industry for case -1 with a change in γ value ... 120
7.2.2 Analysis for the cartridge manufacturing industry for case -2 with a change in γ value ... 122
7.2.3 Analysis for the cartridge manufacturing industry for case-2 with a
change in α value ... 125
7.2.4 Analysis for the tire manufacturing industry for case -1 with a change in γ value ... 129
7.2.5 Analysis for the tire manufacturing industry for Case -2 with a change in γ Value ... 131
7.2.6 Analysis for the tire manufacturing industry for case -2 with a change in α value ... 134
7.3 Results and discussion for ―Modeling the RSC Inventory‖ ... 138
7.4 Results and analysis for ―A probabilistic approach for RSC model for remanufacturing‖ ... 143
7.5 Results and analysis for ―A Modified RSC with remanufacturing for sustainable product cycle‖ ... 146
7.6 Results and Analysis for ANFIS ... 150
7.6.1 Tire manufacturing case-1 ... 150
7.6.2 Tire manufacturing case-2 ... 155
7.6.3 Cartridge manufacturing case-1 ... 161
7.6.4 Cartridge manufacturing case -2 ... 165
7.7 Summary ... 171
8 CONCLUSIONS AND SCOPE FOR FURTHER WORK ... 172
8.1 Overview ... 172
8.2 Conclusions ... 173
8.3 Limitations ... 174
8.4 Contributions ... 175
8.5 Scope for further work ... 176
9 REFERENCES ... 177
Curriculum Viate ... 189
Published and Accepted Papers ... 190
List of Tables
Table 2-1: Some of the important work on Reverse supply chain management. ... 31
Table 5-1: The values of S, Im and total cost with variation of fraction returned. 104 Table 6-1: Configuration of ANFIS. ... 118
Table 7-1: Change in the value of Qm and Qw with change in the γ value ... 120
Table 7-2: Effect of change in γ value on Qm ,Cbavg, α, Qr and Qw. ... 122
Table 7-3 : Variation of Qm and Qw with α = 0.5... 125
Table 7-4 : Variation of Qm and Qw with α = 0.6... 126
Table 7-5 : Variation of Qm and Qw with α = 0.7... 126
Table 7-6 : Variation of Qm and Qw with α = 0.8... 128
Table 7-7 : Variation of model variables with change in γ value. ... 129
Table 7-8 : Variation of the model variables with γ value. ... 131
Table 7-9 : Variation of Qm and Qw with α = 0.5... 134
Table 7-10 : Variation of Qm and Qw with α = 0.6... 135
Table 7-11: Variation of Qm and Qw with α = 0.7... 136
Table 7-12 : Variation of Qm and Qw with α = 0.8... 137
Table 7-13 : Variation of Total cost using Remanufacturing with fraction return. ... 139
Table 7-14 : Variation of profit with variation in fraction return. ... 140
Table 7-15 : Change in Direct manufacturing quantity, Remanufacturing quantity and Number of cycles required annually with change in fraction return. ... 141
Table 7-16 : Variation of length of operating cycle (in days) with variation in fraction return. ... 142
Table 7-17: The values of S, Im and total cost with variation of fraction returned 144 Table 7-18: Process Parameters for Model Analysis. ... 147
Table 7-19: Comparison of results for case -1 for Tire manufacturing. ... 154
Table 7-20: Comparison of results for case -2 for Tire manufacturing. ... 160
Table 7-21: Comparison of results for case -1 for cartridge manufacturing... 165
Table 7-22: Comparison of results for case -2 for cartridge manufacturing... 170
List of Figures
Figure 1.1: Stages of supply chain. ... 2
Figure 1.2: Cycle view of supply chain process. ... 5
Figure 1.3: Push/Pull Processes for the L.L.Bean Supply Chain... 7
Figure 1.4: Push/Pull processes for Dell supply chain for customized PCs ... 8
Figure 1.5: Framework of reverse supply chain ... 13
Figure 1.6: Remanufacturing cycle ... 18
Figure 1.7: Framework of reverse distribution ... 20
Figure 1.8: Product recovery in reverse supply chain... 23
Figure 3.1: Framework of Remanufacturing System. ... 64
Figure 3.2: The material flow in a simple manufacturing /remanufacturing system ... 64
Figure 3.3: The remanufacturing process showing the main material flows at the Electrolux remanufacturing facility. ... 65
Figure 3.4 : The integrated closed-loop supply chain inventory system. ... 66
Figure 3.5: Single product remanufacturing system within the context of Closed Loop Supply Chain ... 67
Figure 3.6: Single product closed-loop supply chain... 68
Figure 3.7: Remanufacturing system with take-back requirement. ... 69
Figure 3.8: Closed-loop supply chain with production, disposal and remanufacturing ... 69
Figure 3.9: Product life cycle ... 70
Figure 3.10: Conceptual frame work for remanufacturing system. ... 71
Figure 4.1: Model of supply chain with remanufacturing ... 75
Figure 4.2: General reverse supply chain model with remanufacturing. ... 87
Figure 4.3: Proposed supply chain model with remanufacturing ... 88
Figure 5.1 A model with uniform demand rate, finite production rate and shortages allowed ... 95
Figure 5.2 The proposed model with remanufacturing. ... 99
Figure 5.3 The inventory model considering safety stock. ... 102
Figure 5.4 Model setup for remanufacturing and newly procured items to satisfy the market demand. ... 105
Figure 6.1: Architecture of ANFIS ... 115
Figure 6.2: ANFIS model structure. ... 117
Figure 7.1: Change in the value of Qm with corresponding change in γ value. .... 121
Figure 7.2: Change in the value of Qw with corresponding change in γ value ... 121
Figure 7.3: Change in the value of Qm with corresponding change in γ value. .... 122
Figure 7.4: Change in the value of Qr with corresponding change in γ value. ... 123
Figure 7.5:Change in the value of Qw with corresponding change in γ value. ... 123
Figure 7.6: Change in the value of Qw with corresponding change in γ value. .... 124
Figure 7.7: Change in the value of Cbavg with corresponding change in γ value. . 124
Figure 7.8 : Variation of Qm and Qw with α = 0.5... 125
Figure 7.9 : Variation of Qm and Qw with α = 0.6... 126
Figure 7.10 : Variation of Qm and Qw with α = 0.7. ... 127
Figure 7.11 : Variation of Qm and Qw with α = 0.8. ... 128
Figure 7.12 : Change in the value of Qm with corresponding Change in the γ value ... 130
Figure 7.13 : Change in the value of Qw with corresponding Change in the γ value. ... 130
Figure 7.14 : Change in the value of Qm with corresponding Change in the γ value. ... 132
Figure 7.15 : Change in the value of Qr with corresponding change in γ value. .. 132
Figure 7.16 : Change in the value of Qw with corresponding change in γ value. . 133
Figure 7.17 : Change in the value of Cbavg with corresponding change in γ value. ... 133
Figure 7.18 : Change in the value of α with corresponding change in γ value. .... 134
Figure 7.19 : Variation of Qm and Qw with α = 0.5. ... 135
Figure 7.20 : Variation of Qm and Qw with α = 0.6. ... 136
Figure 7.21 : Variation of Qm and Qw with α = 0.7. ... 137
Figure 7.22 : Variation of Qm and Qw with α = 0.8. ... 138
Figure 7.23: The variation of total cost with fraction return... 139
Figure 7.24 : Profit Vs Fraction return... 140
Figure 7.25: Variation of direct manufacturing quantity, Remanufacturing quantity and Number of cycles with fraction return. ... 141
Figure 7.26: Variation of length of operating cycle with fraction return... 143
Figure 7.27: The variation of remanufactured quantity and raw material inventory with fraction of demand. ... 144
Figure 7.28: The variation of quantities for direct manufacturing and remanufacturing with change in fraction of demand return. ... 145
Figure 7.29 : The variation of total cost with fraction of demand. ... 146
Figure 7.30: Effect of order cost (C0) on the system. ... 147
Figure 7.31: Effect of setup cost for remanufacturing (Cs) on the system. ... 148
Figure 7.32: Effect of capacity of recovery process (p) on the system. ... 148
Figure 7.33: Effect of demand rate (d) on the system. ... 149
Figure 7.34: Effect of holding cost for returned items for remanufacturing (Ch1) on the system. ... 149
Figure 7.35: Effect of holding cost for new items (Ch2) on the system ... 150
Figure 7.36: Comparison of predicted and desired value for Qw. ... 150
Figure 7.37: Normal probability plot for Qw. ... 151
Figure 7.38: Residual plot for Qw. ... 151
Figure 7.39: Comparison of predicted and desired values for D2. ... 151
Figure.7.40: Normal probability plot for D2. ... 152
Figure 7.41: Residual plot for D2. ... 152
Figure7.42: Comparison of predicted and desired values for D1. ... 152
Figure 7.43: Normal probability plot for D1. ... 153
Figure 7.44: Residual plot for D1. ... 153
Figure 7.45: Comparison of predicted and desired values for γ. ... 153
Figure 7.46: Normal probability plot for γ... 154
Figure 7.47: Residual plot for γ. ... 154
Figure 7.48: Comparison of predicted value and desired value for Qw. ... 155
Figure 7.49: Normal probability plot for Qw. ... 155
Figure 7.50: Residual plot for Qw. ... 156
Figure 7.51: Comparison of predicted value and desired value for Qr. ... 156
Figure 7.52: Normal probability plot for Qr... 156
Figure 7.53: Residual plot for Qr ... 157
Figure 7.54: Comparison of predicted value and desired value for Cbavg. ... 157
Figure 7.55: Normal probability plot for Cbavg. ... 157
Figure 7.56: Residual plot for Cbavg. ... 158
Figure 7.57: Comparison of predicted value and desired value for α. ... 158
Figure 7.58: Normal probability plot for α. ... 158
Figure: 7.59: Residual plot for α. ... 159
Figure 7.60: Comparison of predicted value and desired value for γ. ... 159
Figure 7.61: Normal probability plot for γ... 159
Figure 7.62: Residual plot for γ. ... 160
Figure 7.63: Comparison of predicted value and desired value for Qw. ... 161
Figure 7.64: Normal probability plot for Qw. ... 161
Figure 7.65: Residual plot for Qw. ... 161
Figure 7.66: Comparison of predicted value and desired value for D1. ... 162
Figure 7.67: Normal probability plot for D1. ... 162
Figure 7.68: Residual plot for D1. ... 162
Figure 7.69: Comparison of predicted value and desired value for D2. ... 163
Figure 7.70: Normal probability plot for D2. ... 163
Figure 7.71: Residual plot for D2. ... 163
Figure 7.72: Comparison of predicted value and desired value for γ. ... 164
Figure 7.73: Normal probability plot for γ... 164
Figure 7.74: Residual plot for γ. ... 164
Figure 7.75: Comparison of predicted value and desired value for Qw. ... 165
Figure 7.76: Normal probability plot for Qw. ... 166
Figure 7.77: Residual plot for Qw . ... 166
Figure 7.78: Comparison of predicted value and desired value for Qr ... 166
Figure 7.79: Normal probability plot for Qr. ... 167
Figure 7.80: Comparison of predicted value and desired value for α. ... 167
Figure 7.81: Normal probability plot for α. ... 168
Figure 7.82: Residual plot for α. ... 168
Figure 7.83: Comparison of predicted value and desired value for Cbavg. ... 168
Figure 7.84: Normal probability plot for Cbavg. ... 169
Figure 7.85: Residual plot for Cbavg. ... 169
Figure 7.86: Comparison of predicted value and desired value for γ. ... 169
Figure 7.87: Normal probability plot for γ... 170
Figure 7.88: Residual plot for γ. ... 170
List of Symbols
D1 Demand rate of new product [unit/time]
D2 Demand rate of remanufactured product [unit/time]
c1 Unit manufacturing cost for new product [Rs/unit]
c2 Unit manufacturing cost for remanufactured product [Rs/unit]
α Return rate of end-of-use products P1 Unit price of new product [Rs/unit]
P2 Unit price of remanufactured product [Rs/unit]
Qh Number of units holding the product [units]
Qs Number of units of new product supply to the market [units]
Qm Number of units of remanufactured product [units]
Qr Number of units of return for end-of use products [units]
Qw Number of units of waste product [units]
a1 Maximum units of sales of new product [units]
a2 Maximum units of sales of remanufactured product [units]
b1 Price sensitive to the customer for new product [Rs/unit]
b2 Price sensitive to the customer of remanufactured product [Rs/unit]
γ Sensitivity to price difference[units/Rs]
cb Unit buy back cost [Rs/unit]
s Scaling factor
d Demand rate
p Production rate
C1 Cost of holding inventory per item per unit time C2 Setup cost per production run for remanufacturing C3 Cost of setting up a production from raw materials q Number of items manufactured per run
q1 Number of items remanufactured per run
t1 Time Interval for the production run from raw materials t11
Time during which the stock is building
t111 Time during which there is no production but consumption of inventory
Im Maximum level of inventory at the end of ―t11
t2 Time during which the remanufactured items are consumed.
K1 Remanufacturing rate.
q Manufactured quantity during the cycle.
K Rate of production (units/year).
R Rate of consumption (units/year).
T1 Time for which there is production/procurement as well as consumption.
T2 Time in which there is only consumption and the stock level comes down to zero.
T3 Time for which the production/procurement starts again realizing the back orders till the stock level comes back to zero.
r The number of returned items collected from customers in unit time (units/time)
p Capacity of the remanufacturing process (units/time) d Demand of finished products/serviceable(units/time) Cs Set up cost for the remanufacturing process (Rs/setup) Co Ordering cost for new items (Rs/order)
Ch1 Inventory holding cost for the returned items for remanufacturing (Rs/unit/time)
Ch2 Inventory holding cost for the newly manufactured items (Rs/unit/time)
T Cycle time.
t Time after which remanufacturing initiates.
Abbreviations
SCM Supply Chain Management MRP Material Requirement Planning B2B Business to Business
B2C Business to Customer
OEM Original Equipment Manufacturer EOL End of Life
SCOR Supply-Chain Operations Reference VRCD Vehicle Recycling Development Center DFD Design for Disassembly
APRA Auto Parts Remanufacturers Association QM Quality Management
SCQM Supply Chain Quality Management ESCM Environmental Supply Chain Management ETO Engineer to Order
TCT Transaction Cost Theory TQM Total Quality Management
BOSC Build-to-order Supply Chain Management SMEs Small and Medium Enterprises
C hapter 1
1 INTRODUCTION
1.1 Overview
Over the past decade, there has been an increasing emphasis on supply chain management as a vehicle through which firms can achieve competitive advantage in markets. A large number of examples in the 1990s show how companies have made large investments to streamline their supply chains in order to improve customer satisfaction and increase their internal productivity. As Christopher [1]
states, it is not actually individual companies that compete with each other now a days; rather, the competition is between rival supply chains. The supply chains that add the most value for customers with the lowest cost in the chain make up the winning network of individual companies.
Supply chain management offers an integrated philosophy for managing organizations purchasing and distribution processes based on a marketing perspective. Supply chain management is a homogenous management concept. The overall objective of supply chain management is to contribute to improvements in the company‘s bottom line or profitability. Related objectives include reducing the costs mainly by reducing the inventory level and increasing the revenues by improving customer service through coordination and integration along the material flow, win-win relationships and end customer focus. These imply that in order to achieve the objectives of supply chain management individual companies should coordinate and integrate their activities with other companies along the material flow in win-win relationships and focus their joint effort on the end customer. The supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request. In addition to the manufacturer and suppliers, supply chain includes transporters, warehouses, retailers and customers. All the functions,
fulfilling the customer request are included by the supply chain within the organization. The functions like new product development, marketing, operations, distribution, finance, and customer service are encompassed within these functions.
In order to maximize the total profitability, supply chain management coordinates the management of flows between and within the stages of supply chain.
Supply chain management is the integration and management of supply chain organizations and activities through cooperative organizational relationships, effective business processes, and a high level of information sharing to create high performing value systems that provide member organizations sustainable competitive advantage.
Supply chain can be thought of the involvement of one player at each stage of the organization. In real case scenario, the material flow in manufacturing organization is a transaction between several suppliers to several distributors creating a supply chain network. Therefore, it is more accurate to use supply network or supply web to define the organization of supply chain, as shown in Fig. 1.1.
Figure 1.1: Stages of supply chain.
Directly or indirectly, the supply chain includes all the events, in fulfilling the customer request. SCM entangles challenges in developing trust and collaboration among supply chain allies, identifying best practices that can facilitate supply chain process alignment and integration, and successfully implementing the latest collaborative information systems and Internet technologies that drive efficiencies, performance, and quality throughout the supply chain. Network design in supply
Supplier Manufacturer Distributor Retailer Customer
Supplier Manufacturer Distributor Retailer Customer
Supplier Manufacturer Distributor Retailer Customer
chain and demand forecasting in a supply chain are the main role in supply chain management. Industries and organizations in any supply chain must make decisions individually and collectively regarding their actions in five specific areas:
Production: What products does the market would like? How much and when of which products should be produced? This activity includes the creation of master production schedules that take into account capacity planning, workload balancing, quality control, and equipment maintenance management.
Inventory: How much and when? What inventory should be stocked and when at each stage in a supply chain? How much inventory should be held as raw materials, semi- finished goods, finished goods and work in process? The primary purpose of inventory is to act as a cushion against uncertainty in the supply chain. As holding inventory can be expensive, hence the optimal inventory levels and reorder points are much important.
Location: Where should facilities for inventory storage and manufacturing be located? What are the most cost efficient locations for manufacturing and inventory storage? Whether existing facilities be used or new ones built? These decisions determine the possible paths available for product to flow through for delivery to the end user.
Transportation: Transportation refers to the movement of inventories from one location to another as it makes its way from the beginning of a supply chain to the end users. Most of the manufacturers & retailers have an intention to use state of the art supply chain management to reduce inventory & warehousing costs while speeding up delivery to the end customer. Air freight and truck delivery are generally fast and reliable but they are expensive on the other hand.
Much less expensive methods like, Shipping by sea or rail but it usually involves longer transit times and more uncertainty. This uncertainty must be compensated for by stocking higher levels of inventory. Which mode of transportation to be used and when the key to success in field of supply chain management.
Information: This particular area is related to data collection and information sharing. How much data should be collected and how much information should be mutual? Precise and timely information holds the guarantee of better coordination and better decision making. Without good information, people can
never make effective decisions about what to produce and how much, about where to locate inventory and how best is to transport it.
1.2 Process views of a supply chain
The organization of Supply chain is a network of processes and flows taking place between and within different stages and optimize it to fill the customer need for a product.
The processes executed in a supply chain can be viewed in two different ways.
1. Cycle View: The processes in a supply chain network are divided into a number of cycles and each cycle is accomplished at the interface between two consecutive stages in the network.
2. Push/Pull View: Different processes in the supply chain are divided into two categories depending on whether they are initiated in response to the customer requirement (make to order) or expecting the customer requirement (make to stock).The make to order initiated by customer order are the pull processes and make to stock in anticipation of customer order are the push processes.
1.2.1 Cycle view of supply chain processes
All supply chain processes can be broken down into the following four process cycles considering the five stages of a supply chain shown in Fig 1.2[ 2 ],
Customer order cycle
Replenishment cycle
Manufacturing cycle
Procurement cycle
Each cycle is executed at the interface between two consecutive stages of the supply chain. It includes four detectable cycles within five stages which depends on the type of organization. In a grocery supply chain, the retailer maintains stock of finished goods and places renewal orders with distributor that includes all four cycles but in contrast to it, Dell bypassing the retailers and distributors, sells directly to the consumers. The six sub processes per cycle is given below
Supplier stage that markets the product
Buyer‘s stage that places order
Supplier stage that receives order
Supplier stage that supplies order
Buyer stage that receives supply
Buyer returns reverse flows to supplier or the third party.
In each cycle, the sub-processes are linked in a definite way that starts with the supplier marketing the product to customers. The buyer then places an order which is received by the supplier. Then the supplier supplies the order that is received by the buyer. Some of the products or other recycled materials may be returned by the buyer to the third party or supplier. The cycle of activities is repetitive. The final aim of the buyer, within each cycle is to guarantee product availability and to accomplish economies of scale in ordering a product.
Figure 1.2: Cycle view of supply chain process.
In the process of forecasting the customer order and cost of receiving the order the responsibility of the supplier lies in fulfilling the order in time while taking care of
Customer
Supplier Retailer
Distributor
Manufacturer Customer Order Cycle
Replenishment Cycle
Manufacturing Cycle
Procurement Cycle
the efficiency improvement and truthfulness of order replenishment process. The reduction of cost of receiving process is worked out by the buyer. To manage reduction of cost and meet environmental objectives, reverse flows are encouraged.
Each cycle has the identical basic sub processes with a few key differences between different cycles. Demand, being external to the supply chain is uncertain.
In order cycle the uncertainty lies in the order placement but it can be forecasted on the basis of policies framed by a supply chain network
1.2.2
Push/Pull view of a supply chain processesAll processes in a supply chain fall into one of the two categories depending on the timing of their execution in response to the demand of the end user. In the pull type processes, execution is initiated in response to the end user‘s order (make to order).
But in the push type processes, execution is initiated in anticipation of end user‘s orders (make to stock). The pull processes are executed with a definite demand as the customer requirement is known, whereas the push processes are accomplished with an uncertain demand scenario as the demand has to be forecasted. As the pull processes react to the actual requirement of the customers, these are referred as reactive processes. Push processes are rather speculative in nature and referred as speculative processes as they respond to the speculative/forecasted demand. A clear demarcation in a supply chain between push and pull processes of L.L. bean is shown in fig. 1.3.The operational environment of push and pull processes lies in the uncertainty and certainty of the customer demand respectively. The pull system is easy to operate from the supply chain point of view. However there are certain restrictions imposed on the push system in the form of inventory and the capacity decision.
The execution of all processes in customer order cycle in L.L.Bean [2] takes place after the customer arrives. Hence all the processes in the customer order cycle are Pull processes. The fulfilment of the order takes place from the product in inventory. The processes in the replenishment cycle are performed in anticipation of the market demand thus a push processes.
The scenario is completely different in Dell [2] where customized computers are built to order.
There is no reseller or distributor in the network and Dell sells directly to the customers.
Figure 1.3: Push/Pull Processes for the L.L.Bean Supply Chain
Demand is filled from production and not from the finished product inventory. Dell operates on two cycles as shown in Fig 1.4
Customer order and manufacturing cycle and
Procurement cycle.
At Dell, all the processes in the Customer order and manufacturing cycle are thus pull processes as they are triggered by customer arrival. The push processes are the processes related to procurement cycle as they are in response to the demand forecast.
A push/pull view of supply chain is very useful when considering strategic decisions relating to supply chain design. To match the supply and demand effectively, the goal of the organization is to identify an appropriate push/pull boundary.
PULL PROCESS
PUSH PROCESS Customer Order Arrives Customer
Order Cycle
Procurement, Manufacturing, Replenishment Cycle
Customer Order Cycle
Replenishment and Manufacturing Cycle
Procurement Cycle
Customer
L.L.Bean
Manufacturer
Supplier
Figure 1.4: Push/Pull processes for Dell supply chain for customized PCs
1.3 Reverse supply chain
The weakening conditions of the environment, reduction of non-renewable resources, and the constantly increasing land fill of waste have forced organizations and communities to consider recovery alternatives such as reuse, repair, recycle, refurbish, remanufacture and cannibalize, rather than discarding of the products after end of life. In order to facilitate and support the recovery process, the basic pattern of the entire supply chain needs to be redefined so that related environmental concerns can be minimized. Therefore the reutilization of resources and integration of the upstream and downstream chains is highly essential.
Since long, firms are rigorous on getting products and services to the market and the amount of scientific assistance as well as business practices for the forward supply chain are largely explored. Contributions exploring the potential of the reverse flow from a practical point of view are relatively little. Whilst the tools and techniques like MRP, bullwhip effect, just-in time, lean production, mass customization, delayed product differentiation have been extensively explored both from a theoretical and operational point of view, a very few attempts has been made pertaining to the reverse supply chain, imparting the same knowledge. In evaluating reverse logistics tasks, the focus has traditionally been in minimizing costs ensuring a reasonable customer service and satisfaction. Over time, the recognition of the increasing value of products and technology created in the field at the end of the direct supply chain and the impact of the environmental legislation has forced companies to focus on different types of recovery programs.
Customer order and manufacturing cycle Pull
processes
Push processes Customer order arrival Customer order
and
manufacturing
Procurement cycle
Procurement cycle
1.4 Product returns: the various routes
In general, products are retuned back or become redundant because either they do not function properly or functionally they become obsolete. Therefore it becomes important to know the return reasons with usual supply chain stages starting with manufacturing, distribution and finally product reaching the customer. Therefore the returns can be divided under three heads like manufacturing returns, distribution returns and customer returns.
1.4.1 Manufacturing returns
Manufacturing returns encompass all those returns for which the need for recovery of components or products is identified during the production phase. This occurs for a number of reasons. left over raw materials, intermediate or final products not passing through quality checks and have to be reworked and products left over during production, or by-products resulting from production are the major reasons for manufacturing returns. The raw material surplus and production leftovers represent the ‗product not-needed‘ category, while quality-control returns fit in the do not function category. Hence, manufacturing returns include:
• Raw material surplus
• Quality-control returns
• Production leftovers/by-products 1.4.2 Distribution returns
Distribution/supply returns refers to all those returns that are triggered during the distribution phase. It refers to stock adjustments, commercial returns, product recalls, and functional returns. A stock adjustment is the redistribution of stocks in the supply chain. Stock adjustments can occur between warehouses or shops for example in the case of seasonal products [3]. B2B commercial returns are all those returns for which a buyer has a contractual option to return products to the seller [4]. This can refer to wrong/damaged deliveries or to unsold products that retailers or distributors return to, e.g. the wholesaler or manufacturer. The latter includes out-dated products. This includes the products having a very short shelf life (perishable items) like, pharmaceutical products and food items. While the stock adjustments occur within a company, the commercial returns involve more than one company alone. Product recalls are products recollected because of safety or health problems with the products, and are initiated by the manufacturer or a supplier, and not the customer [5]. Product recalls fall in ‗distribution returns‘ as
they are usually initiated during this phase and they are anyway specially demanding with respect to distribution. Finally, there are products for which their inherent function makes them go back and forward in the chain. One can suggest calling these as ‗functional returns‘. An obvious example is distribution carriers like pallets: their function is to carry other products and they can serve this purpose several times [6, 7]. Summarizing, distribution returns comprehend:
stock adjustments
B2B commercial returns
product recalls and
Functional returns (distribution items/carriers/packaging).
1.4.3 Customer returns
The customer returns comprises of returns initiated by the customers once the product has reached the final customer. This happens due to a number of reasons.
B2C commercial returns (reimbursement/other guarantees),
warranty returns,
Service returns (repairs, spare-parts, etc.),
end-of-use returns, and
End-of-life returns.
As much as possible, the reasons have been listed according to the life cycle of a product. B2C commercial returns, like reimbursement guarantees, give customers the opportunity to change their minds about purchasing when their needs or expectations are not met (usually shortly after having received/ acquired the product). The list of underlying causes is long. For Reverse Logistics, questionnaires like why, what, how and who plays a vital role in finding out the causes of return. Independent of the underlying causes, when a customer returns a new product, benefiting from a money-back-guarantee or an equivalent, there lies the presence of B2C commercial returns. The next two reasons, warranty and service returns, refer mostly to an incorrect functioning of the product during use, or to a service that is associated with the product and from which the customer can benefit. Initially, customers benefiting from a warranty can return products that do not (seem to) meet the promised quality standards. Sometimes, these returns can be repaired. Otherwise, a customer may get a new product or his/her money back after which the returned product can be recovered. After the warranty period has
expired, customers can still benefit from maintenance or repair services, but they no longer have the right to get a substitute product for free. Products can be repaired at the customer‘s site or sent back for repair. In the former case, returns commonly occur in the form of spare parts, since in advance it is hard to know precisely which components are going to be needed for the repair. End-of-use returns refer to those situations where the user has a return opportunity at a certain life stage of the product. This refers to leased products and returnable containers like bottles, but also to returns to second-hand markets as the one of Biblio find, a division of Amazon.com for used books (see Amazon.com, online). Finally, end- of-life returns refer to those returns for which the product as such is at the end of its economic or physical life. They are either returned to the OEM because of legal product-take-back obligations, or other companies like brokers, collect them for value-added recovery. Summarizing the typology ‗return reasons‘ for reverse logistics in the three stages of a supply chain: manufacturing, distribution, and customer.
One should note however that the distinction between these three stages might be factitious. In practice it is not always easy to pinpoint exactly where manufacturing ends and distribution starts, as value may be added when some sort of distribution has already begun.
Recovering parts for reuse, repair, recycle, refurbish, remanufacture and cannibalize are the examples of reverse logistics having an attractive business opportunity and emphasizing sustainability. ―…by ignoring the efficient return and refurbishment or disposal of product, many companies miss out a significant return on investment‖. Way back 1970; the supply chains were busy in fine-tuning the logistics of products from raw material to the end customer. Now also the Products are still streaming in the direction of the end customer but an increasing flow of products is coming back to the manufacturer. This is taking place for a wide range of industries. The major industries coming under this covers pharmaceuticals, electronic goods, beverages, sponge iron etc. the automobile industry is demanding the change in the physical and virtual supply chain to facilitate end-of-life recovery [9]. It is not surprising that the Reverse Logistics Executive Council has announced that US firms have been losing billions of dollars on account of being il l prepared to deal with reverse flows [10]. The return as a process was recently added to the Supply-Chain Operations Reference (SCOR) model, stressing its importance for supply chain management in the future[11]. There is a trend of recycling that is
stretching out worldwide, involving all the layers of supply chains in various industry sectors. As some performers in the chain have been forced to take products back, others, attracted by t h e value in the used products return have positively done so. With much less ambiguity, reverse Logistics has become a key competence in the field of supply chain.
Though the inception of Reverse supply chain germinated out from long time ago, the very term is difficult to trace with precision and accuracy. Synonymous terms like Reverse Channels or Reverse Flow already appear in the scientific literatures way back in the seventies, but predominantly related with recycling [12, 13].During the next decade, the definition was inspired by the movement of flows against the conventional flows in the supply chain, as put by Lambert and Stock [ 1 4 ] . In the early nineties, a more logical and formal definition of Reverse logistics, a subset of reverse supply chain was put together by the Council of Logistics Management, stressing the recovery aspects of reverse logistics [15-18]. Logistics has been defined as that part of the supply chain process that plans, implements, and controls the efficient, effective flow and storage of goods, services, and related information from the point-of-origin to the point-of-consumption in order to meet customers‘ requirements. Reverse logistics has been defined as the movement of product or materials in the opposite direction for the purpose of creating or recapturing value, or for proper disposal [19]. The reverse flow may consist of both product and packaging, and both have been studied in the literature.
In summary, the definition of Reverse supply chain has changed over time, starting with a sense of "wrong direction." going through an overemphasis on environmental aspects, coming back to the original pillars of the concept, and coming finally to a widening of its scope. For other discussions on the evolution of the definition of Reverse supply chain put forth by Fernandez [20] can be referred.
Figure 1.5: Framework of reverse supply chain
1.5 The Forward Supply Chain vis-à-vis Reverse Supply Chain
There lie a lot of differences between Forward and Reverse supply chains that rationalize the development of different theories for each region. For the scope of this work, the focus is mainly based on the analysis for the operations management issues of Reverse supply chain. It is worth noting that, all the organizational areas may be affected by the introduction of a Reverse supply chain system into a company. To investigate the differences between forward and reverse Supply Chain the following areas of work are being considered:
Location theory and logistics network design
Forecasting
Inventory control
Production /Remanufacturing
Disassembly operations
Reverse Distribution.
Production waste Commercial return
EOL Return Supply of
raw material
Manufacturing
Distribution
Consumer
Collection Selection
Disposal Reuse
Remanufacture Refurbish Cannibalize
Recycle Redistribution
1.5.1 Location theory and logistic network design
This research area comprises of all the design of the reverse network. Primarily, it is concerned with the optimization of the location and capacity of the facilities and the flow of goods between them as well. The demands and operational costs are considered inputs to the location models in the conventional models. Since the secondary markets, disposal facilities, etc. also receive the product of the company in Reverse supply chain, the demands are located not only at one side of the chain but in both. Krikke [21] considers some elements that differentiate the Reverse supply chain network design from the forward one:
―Forward logistics systems are pull systems, while in reverse supply chain there is a combination of push and pull, due to the fact that there are clients on both sides of the chain, namely the disposer and the re-user. In forward logistics, only customer markets need to be served and the entire logistic chain, including suppliers (the ‗equivalent‘ of disposers), adjusts itself to it. As a result of the extended producer responsibility, the amount of waste supplied to the reverse supply chain system (the push) cannot be influenced in the long run and has to be matched with demand (the pull). Disposal can serve as an escape route for unwanted waste, but the amount of disposal is limited by legislation.‖
Opposing to the divergent nature of forward supply chain, the reverse supply chain networks are both converging and diverging in nature. The return flows in the reverse supply chain are diverted into different processes like Repair, refurbishing, remanufacturing, cannibalization and recycling where the discarded/returned/EOL products are transformed into materials, components and secondary products. In contrast to it, in the forward supply chain there is the production unit where transformation takes place which serves as a source in the forward network.
The transformation process in reverse supply chain tends to be incorporated in the distribution network that covers the whole production process starting from the disposal to reuse. As only a fraction (not properly defined) of the return items are being used, an efficient design, operation and control spread over a high number of
stratum. But the forward supply chain usually considers one or two levels.
Fleischmann et al. [22] in addition state the following difference:
―A particularity in the reverse distribution networks is their high degree of uncertainty in supply, both in terms of quantity and quality of used products returned by the consumers. Both are determinants for a suitable network structure since, e.g. high quality products may justify higher transportation costs (and thus a
more centralized network structure), whereas extensive transportation of low value products is uneconomical. Moreover, end-markets for recovered products may not be well known, exposing network planning in this context to even more uncertainty.‖
There is always a uncertainty associated with the product return. Therefore it is difficult to make an assessment to the number and quality of the returned items until it is received. This type of situation makes the design of the logistic network more complex as the details of the demand are not available in advance. One can approximate the quantity of the returned items but the quality of the same remains a question mark.as the worth of the product is influenced by the quality and quantity of the returned items directly; it influences the decision of location and distribution.
One of the major issues in decision making is to stabilize the reverse network.
Always there remains a trade-off of the returns through a centralized facility and different facilities close to the client‘s premise. Another characteristic issue that always puts the management decision in fix is whether to manage the RSC with the same facilities with which the forward supply chain is managed with.
1.5.2 Forecasting
The solution to the problem of forecasting is a difficult task in reverse supply chain. This activity consists in the estimation of the magnitude, timing, location and quality of the returns received. Many a times, returns arise from demand forecasting errors. Again, inaccurate forecasting may lead to some problems that emerge in the reverse supply chain activities. Looking at the other side, the lack of information of some secondary markets makes it difficult to estimate the number of buyers in those markets. Considering some areas like secondary packaging return, forecasting is addressed by considering the system as a closed loop, where the same elements are present in the system and there are some loses at each cycle.
This approach helps forecasting since the problem is reduced to estimate the number of units lost at each cycle of the product. For secondary packaging is a good way of forecast, since the idea is to recover the entire package sent.
Nevertheless, there is still a lack of established models available in this area.
1.5.3 Inventory control
To manage the return inventory effectively is also considered an important issue.
The management of inventory has become more difficult with some identifiable issues when returns are integrated to the manufacturing processes.
Ambiguity in the quantity of products received may result in excess stock or end up with stock out easily.
Since the bar code is frequently worsened in returned items, it becomes difficult in identifying some articles.
The occurrence of the following cases in some segments is frequent. The products with promotional offer are considered as new and dispatched to the market with a new code. At the time of return, without the promotional object these products are merged with the inventory with a different code of a single object. This complication generates problem of inventory balance while dealing with these cases.
Reasons, apart from these are also available to develop new models for the inventory management of the returns: Krikke [21] says that ―Inventory management in product recovery situations is particularly different in those which are closed loop. In the remanufacturing environment, the increased system complexity and uncertainty resulting from interactions between forward and return flows, requires adapted control mechanisms‖. Fleischmann et al. [22] state three differences between reverse and forward logistics inventory control:
In reverse supply chain, as a consequence of the return flow, the inventory level between new component replenishments is no longer necessarily decreasing but may increase also.
This loss of monotonicity significantly complicates the underlying mathematical models.
A possible starting point for a closer analysis of this aspect, are the cash balancing models comprising in and outbound flows.
When returns of goods and remanufacturing options have to be taken into consideration in inventory control situations, two additional sources of complexity appear in the traditional approaches of optimizing stochastic inventory control.
Firstly, due to uncertainty of returns, an additional stochastic impact has to be regarded. Secondly, with remanufacturing a second mode of supply of serviceable goods is given, so that coordination with the regular mode of procurement becomes necessary. It can be shown that under these conditions one faces extremely
complicated optimal control rules if the lead-times for remanufacturing and regular procurement differ. This holds for both the structure of the control policy and the inventory information necessary for optimal stock adjustment. In this context, the meaning of the inventory position, which is well-defined in traditional inventory control, is no longer evident. In practice, in these situations usually simple (suboptimal) decision rules are applied that only use a few control parameters and additionally do not take into consideration the complexity of defining the inventory position appropriately. For such a simple (4-parameter) control rule it is shown that by determining the inventory position in a proper way the performance of the policy can be improved considerably. This effect is equivalent to using the remanufacturing lead-time as a decision variable which has to be fixed in an optimal way.
1.5.4 Remanufacturing
Disassembly, remanufacturing and reassembly are the three different subsystems that build the foundation of the recoverable manufacturing system. The problems in this area arise as new products are manufactured using three kinds of components in remanufacturing:
Recovered Components from returned products with uncertainty in quantity.
Newly purchased Components.
Contingent to availability and costs, components that can either be purchased new or recovered from returned products.
Krikke [21] shows some reasons for which traditional MRP-systems are not feasible for recovery situations: The primary problem is the bad fit of supply and demand. This is due to the concurrent release of desired and undesired components in the disassembly of returned items. A second most important problem is the compromise between reusing return components and using components outside procurement.
The management, planning, and control of RSC functions have become complex because of six characteristics, Guide et al. [23]. They are:
The uncertainty in timing and quantity of returns.
The need to balance demands with returns, that is supply demand balance.
The necessity to disassemble the returned products.
The uncertainty in materials recovered, that is related to the condition of return items
The need for a reverse supply chain network for the existing process. and
The difficulty of material matching restrictions.
Figure 1.6: Remanufacturing cycle
An additional problem arising from a remanufacturing environment is that to manufacture a product the production path is uncertain, since depends of the returned materials and parts.
Remanufacturing offers tremendous untapped opportunities for businesses, consumers, work forces and the society as a whole. The most prominent beneficiaries of a successful and well managed remanufacturing process are given below.
Business enterprises
Reduction in capital investment expenditure; and
Remarketing of the remanufactured products as a business strategy can increase profit.
Consumers
Lower prices in the order of 30-40 percent less than similar new products;
and
Finished goods Customer Waste
Return collection Test and inspection
Land fill
Remanufacturable items
Remanufacturing Production
